For a HMM, the hidden states are {bull, bear}, the observation variables are {rise, fall}, the initial state probability distribution is [0.5 0.5]¹, the transition probability distribution A is [0.4 0.7; 0.6 0.3], and the observation probability distribution B is [0.8 0.1;0.2 0.9]. If the observation sequence is {fall fall rise}, please show the computation procedure for estimating the most likely state sequence?
For a HMM, the hidden states are {bull, bear}, the observation variables are {rise, fall}, the initial state probability distribution is [0.5 0.5]¹, the transition probability distribution A is [0.4 0.7; 0.6 0.3], and the observation probability distribution B is [0.8 0.1;0.2 0.9]. If the observation sequence is {fall fall rise}, please show the computation procedure for estimating the most likely state sequence?
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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For a HMM, the hidden states are {bull, bear}, the observation variables are {rise, fall}, the initial state probability distribution is [0.5 0.5]¹, the transition probability distribution A is [0.4 0.7; 0.6 0.3], and the observation probability distribution B is [0.8 0.1;0.2 0.9]. If the observation sequence is {fall fall rise}, please show the computation procedure for estimating the most likely state sequence?
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